We’ll be soon at the Ecology and Agriculture Summit for Young scientists

Yes! It is organised by INRA (France) and will take place during the 22-24 March 2017, at the CEBC-Chizé. You can find more information clicking here.

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The project will be represented by Javier Fernandez-de-Simon and Virgile Baudrot, who has worked for the project during January and February. We have submitted these two abstracts with preliminary results. They have been already accepted by the organisation 🙂

 

Do anticoagulant rodenticides affect the seasonal population dynamics of small mustelids?

Prey controlled with pesticides can indirectly poison predators. However, pesticides’ effects on predator dynamics has not been well documented.

Temporal variations of small mustelid (weasels, stoats) abundance follow those of voles, their main prey. Grassland voles show population cycles, damaging pastures/hay fields. Some farmers control voles using anticoagulant rodenticides (ARs), poisoning non-target species feeding on intoxicated voles, like small mustelids. Whether this impacts their populations is not well known.

Here, we study whether bromadiolone (an AR) affects small mustelid populations. Our hypothesis was that ARs decrease small mustelid abundance (SMA) by direct killing/prey declines. Using data of bromadiolone use (2008-2016), we selected 6 sites with no/very low treatment frequency, and 4 with high frequency. We estimated SMA, water vole (WVD) and common vole (CVD) densities in spring and autumn 2016, treatment periods. We estimated the abundance of foxes (FA) as small mustelids’ superpredators.

We calculated the seasonal population change (SPC) of small mustelids as

SPC = Ln (autumn SMA/spring SMA)

SPC was modelled against bromadiolone treatments and other species’ abundance.

All sites with high bromadiolone use showed negative SPC i.e. decreases in population abundance (mean SPC high bromadiolone use= -4.52, mean SPC no/low bromadiolone use= 0.4). Additionally, SPC was positively associated to WVD. Small mustelid abundance decreased at low water vole density but at higher water vole densities small mustelid abundance remained stable i.e. SPC close to 0. Finally, SPC was not related to the other variables (CVD, FA). Results point out that ARs may affect small mustelid population dynamics.

 

Is anticoagulant rodenticide use disrupting the natural regulation of vole populations? A biomathematics modelling approach

Since the 1950’s, world technological/socio-economic changes led to increased pesticides’ use. Understanding pesticides’ impact at several temporal/spatial scales and at communities/ecosystems levels is still challenging.

Grassland small mammals like voles can reach hundreds of individuals/ha, being perceived as pests. Anticoagulant rodenticides (ARs) are used to control voles during the low density and increase phases of their population cycles. Thus, ARs may act as a super-predator, interfering with the natural regulation of vole populations and contaminating vole predators indirectly by eating intoxicated voles. Secondary poisoning of abundant predators has been observed (e.g. foxes), but the effect on elusive small mustelids is unknown.

Here, our objective was to explore the interactions between (i) ARs use (quantity, frequency and period) to control voles, (ii) intraguild predation/competition and (iii) secondary poisoning on predators. We consider small mustelids (stoats, weasels), that mostly eat voles, and generalist (foxes) predators with mainly voles and to a lesser extend mustelids as food items. We used differential equations to explore scenarios on chronic or acute episodes of spread of ARs and combining animal population dynamics, predator-prey interactions, and transfer of bromadiolone across the trophic chain.

Our preliminary results show time lagged appearance of ARs peaks along the trophic levels, illustrated by different delays in population responses to ARs treatments. Though based on a simplified model, our simulations allows to identify which parameters were relevant to reach consensus between agricultural and conservation purposes. Thus, this modelling approach, tightly coupled with field research, provide baselines for optimal farming practices.

 

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